Joint DOA and Polarization Estimation with Sparsely Distributed and Spatially Non-Collocating Dipole/Loop Triads

This paper introduces an ESPRIT-based algorithm to estimate the directions-of-arrival and polarizations for multiple sources. The investigated algorithm is based on new sparse array geometries, which are composed of three non-collocating dipole triads or three non-collocating loop triads. Both the inter-triad spacings and the inter-sensor spacings in the same triad can be far larger than a half-wavelength of the incident sources. By adopting the ESPRIT algorithm, the eigenvalues of the data-correlation matrix offer the fine but ambiguous estimates of the direction-cosines for each source, and the eigenvectors provide the estimates of each source's steering vector. Based on the constrained array geometries, the fine and unambiguous estimates of directions-of-arrival and polarizations are obtained. Simulation results verify the efficacy of the investigated approach and also verify the aperture extension property of the proposed array geometries.Comment: 17 pages, 5 figure

Coherent Sources Direction Finding and Polarization Estimation with Various Compositions of Spatially Spread Polarized Antenna Arrays

Various compositions of sparsely polarized antenna arrays are proposed in this paper to estimate the direction-of-arrivals (DOAs) and polarizations of multiple coherent sources. These polarized antenna arrays are composed of one of the following five sparsely-spread sub-array geometries: 1) four spatially-spread dipoles with three orthogonal orientations, 2) four spatially-spread loops with three orthogonal orientations, 3) three spatially-spread dipoles and three spatially-spread loops with orthogonal orientations, 4) three collocated dipole-loop pairs with orthogonal orientations, and 5) a collocated dipole-triad and a collocated loop-triad. All the dipoles/loops/pairs/triads in each sub-array can also be sparsely spaced with the inter-antenna spacing far larger than a half-wavelength. Only one dimensional spatial-smoothing is used in the proposed algorithm to derive the two-dimensional DOAs and polarizations of multiple cross-correlated signals. From the simulation results, the sparse array composed of dipole-triads and loop-triads is recommended to construct a large aperture array, while the sparse arrays composed of only dipoles or only loops are recommended to efficiently reduce the mutual coupling across the antennas. Practical applications include distributed arrays and passive radar systems.Comment: 40 pages, 18 figures, to appear in Signal Processin